The present invention relates to data anonymity, and more specifically, to a technique for ensuring anonymity of data.
Due to the rapid progress in information technologies, organizations such as companies can nowadays collect and store huge amounts of data in database. For the huge amount of data, automatic or semiautomatic tools which employ data mining techniques have been widely used in order to support data analysis. However, the public become more concerned with a privacy problem. Accordingly, companies need to compromise privacy of data.
The existing techniques of anonymization include the k-anonymization. The k-anonymization is a privacy-preserving approach for minimizing the information loss caused by the k-anonymization.
In a medical field, the digitization of medical charts has been widely performed in recent years, especially, in a large medical institution. Medical data including electronic medical charts is daily updated by entering and leaving hospital.
In some cases, tracing time-series changes is intended to be performed also on the data having been subjected to k-anonymization at certain period intervals. For example, it is desired to trace data taken before and after the onset of a disease. However, tracing the consistency of the data has the risk of losing the anonymity of the data because of a decrease in members of a cluster.